U-shaped fusion convolutional transformer based workflow for fast optical coherence tomography angiography generation in lips

Oral disorders, including oral cancer, pose substantial diagnostic challenges due to late-stage diagnosis, invasive biopsy procedures, and the limitations of existing non-invasive imaging techniques. Optical coherence tomography angiography (OCTA) shows potential in delivering non-invasive, real-time, high-resolution vasculature images. However, the quality of OCTA images are often compromised due to motion artifacts and noise, necessitating more robust and reliable image reconstruction approaches. To address these issues, we propose a novel model, a U-shaped fusion convolutional transformer (UFCT), for the reconstruction of high-quality, low-noise OCTA images from two-repeated OCT scans. UFCT integrates the strengths of convolutional neural networks (CNNs) and transformers, proficiently capturing both local and global image features. According to the qualitative and quantitative analysis in normal and pathological conditions, the performance of the proposed pipeline outperforms that of the traditional OCTA generation methods when only two repeated B-scans are performed. We further provide a comparative study with various CNN and transformer models and conduct ablation studies to validate the effectiveness of our proposed strategies. Based on the results, the UFCT model holds the potential to significantly enhance clinical workflow in oral medicine by facilitating early detection, reducing the need for invasive procedures, and improving overall patient outcomes.</p

U-shaped fusion convolutional transformer based workflow for fast optical coherence tomography angiography generation in lips

Oral disorders, including oral cancer, pose substantial diagnostic challenges due to late-stage diagnosis, invasive biopsy procedures, and the limitations of existing non-invasive imaging techniques. Optical coherence tomography angiography (OCTA) shows potential in delivering non-invasive, real-time, high-resolution vasculature images. However, the quality of OCTA images are often compromised due to motion artifacts and noise, necessitating more robust and reliable image reconstruction approaches. To address these issues, we propose a novel model, a U-shaped fusion convolutional transformer (UFCT), for the reconstruction of high-quality, low-noise OCTA images from two-repeated OCT scans. UFCT integrates the strengths of convolutional neural networks (CNNs) and transformers, proficiently capturing both local and global image features. According to the qualitative and quantitative analysis in normal and pathological conditions, the performance of the proposed pipeline outperforms that of the traditional OCTA generation methods when only two repeated B-scans are performed. We further provide a comparative study with various CNN and transformer models and conduct ablation studies to validate the effectiveness of our proposed strategies. Based on the results, the UFCT model holds the potential to significantly enhance clinical workflow in oral medicine by facilitating early detection, reducing the need for invasive procedures, and improving overall patient outcomes.</p

Abundant off-axis hydrothermal activity in the 29–30 ridge segment of the Southwest Indian Ridge: evidence from ferromanganese crusts

In the ultra-slow spreading mid-ocean ridge, seafloor hydrothermal ventings mostly occur in the off-axis region. The plume of hydrothermal venting provides Fe, Mn and other metal materials for the growth of ferromanganese crust in the surrounding seamounts, showing unique geochemical characteristics that are different from that of hydrogenetic crust. Based on five samples of ferromanganese crusts, major, trace and rare earth element analysis was carried out to identify their material sources. Combined with the investigation data of water column and seafloor camera photos by deep towed hydrothermal detection system, the potential of hydrothermal activity in the 29–30 ridge segment of the Southwest Indian ridge was evaluated. The results showed that the ferromanganese crust in the study area had significantly higher Fe/Mn value (average 1.9), relatively higher Si and Al contents, and significantly higher Ca/P value (average 9.3),without significant phosphorylation. ferromanganese crust in the study area have significantly lower Co and Ni contents (about 1600 mg/kg on average), and relatively lower Sr, Ba, Pb, Cu, Zr and Mo contents (between 100-1000 mg/kg on average). The contents of W, Th and Te are also relatively low (average content between 10–50 mg/kg); The total rare earth element content of the crust in the study area is relatively low (about 928 mg/kg on average), and the light rare earth is relatively enriched. The standardized rare earth curve of the shale shows a left-leaning pattern as a whole, showing the enrichment of heavy rare earth relative to the shale. The Co content and rare earth element content of the ferromanganese crusts in this area are significantly lower than those of hydrogenetic crusts. The discrimination diagrams of ternary and bivariate material sources reveal that they have mixed hydrothermal and hydrogenetic origins. The three crust samples of S1, S2, and S5 are located within 2 km of the known hydrothermal fields, indicating a correlation between ferromanganese crust and the location of hydrothermal activity. There is no known hydrothermal field near the S3 and S4 stations. Altered rocks and water column turbidity anomalies were found near S3 station, and large areas of altered rocks and suspected hydrothermal biological remains were also found near S4 station, indicating that hydrothermal activity may exist in both areas. In addition to the two new hydrothermal fields identified in this article, the spatial frequency of hydrothermal activity in the study area reaches 15 sites/100 km, which is significantly higher than other well investigated oceanic ridges. Out of the eight hydrothermal fields in the study area, seven are located in the off axis region, mainly because the hydrothermal activity in this area is controlled by high angle and large offset normal faults and one-way detachment faults. This also indicates that the off-axis region of the Southwest Indian Ridge has high potential for hydrothermal activity

Robust Ultrafast Projection Pipeline for Structural and Angiography Imaging of Fourier-Domain Optical Coherence Tomography

The current methods to generate projections for structural and angiography imaging ofFourier-Domain optical coherence tomography (FD-OCT) are significantly slow for prediagnosisimprovement, prognosis, real-time surgery guidance, treatments, and lesion boundary definition.This study introduced a robust ultrafast projection pipeline (RUPP) and aimed to develop and evaluate the efficacy of RUPP. RUPP processes raw interference signals to generate structural projectionswithout the need for Fourier Transform. Various angiography reconstruction algorithms were utilized for efficient projections. Traditional methods were compared to RUPP using PSNR, SSIM, andprocessing time as evaluation metrics. The study used 22 datasets (hand skin: 9; labial mucosa: 13)from 8 volunteers, acquired with a swept-source optical coherence tomography system. RUPP significantly outperformed traditional methods in processing time, requiring only 0.040 s for structuralprojections, which is 27 times faster than traditional summation projections. For angiography projections, the best RUPP variation took 0.15 s, making it 7518 times faster than the windowed eigendecomposition method. However, PSNR decreased by 41–45% and SSIM saw reductions of 25–74%.RUPP demonstrated remarkable speed improvements over traditional methods, indicating its potential for real-time structural and angiography projections in FD-OCT, thereby enhancing clinicalprediagnosis, prognosis, surgery guidance, and treatment efficacy

Robust Ultrafast Projection Pipeline for Structural and Angiography Imaging of Fourier-Domain Optical Coherence Tomography

The current methods to generate projections for structural and angiography imaging ofFourier-Domain optical coherence tomography (FD-OCT) are significantly slow for prediagnosisimprovement, prognosis, real-time surgery guidance, treatments, and lesion boundary definition.This study introduced a robust ultrafast projection pipeline (RUPP) and aimed to develop and evaluate the efficacy of RUPP. RUPP processes raw interference signals to generate structural projectionswithout the need for Fourier Transform. Various angiography reconstruction algorithms were utilized for efficient projections. Traditional methods were compared to RUPP using PSNR, SSIM, andprocessing time as evaluation metrics. The study used 22 datasets (hand skin: 9; labial mucosa: 13)from 8 volunteers, acquired with a swept-source optical coherence tomography system. RUPP significantly outperformed traditional methods in processing time, requiring only 0.040 s for structuralprojections, which is 27 times faster than traditional summation projections. For angiography projections, the best RUPP variation took 0.15 s, making it 7518 times faster than the windowed eigendecomposition method. However, PSNR decreased by 41–45% and SSIM saw reductions of 25–74%.RUPP demonstrated remarkable speed improvements over traditional methods, indicating its potential for real-time structural and angiography projections in FD-OCT, thereby enhancing clinicalprediagnosis, prognosis, surgery guidance, and treatment efficacy

Quantitative Optimization of Hand-Held Probe External Pressure on Dermatological Microvasculature Using Optical Coherence Tomography based Angiography

Optical Coherence Tomography (OCT)-based angiography (OCTA) is a high-resolution, high-speed, and non-invasive imaging method that can provide vascular mapping of subcutaneous tissue up to approximately 2 mm. In dermatology applications of OCTA, handheld probes are always designed with a piece of transparent but solid contact window placed at the end of the probe to directly contact the skin for achieving better focusing between the light source and the tissue, reducing noise caused by minor movements. The pressure between the contact window and the skin is usually uncontrollable, and high external pressure affects the quality of microvascular imaging by compressing the vessels and obstructing the underlying blood flow. Therefore, it is necessary to determine a pressure range to ensure that the vessels can be fully imaged in high-quality images. In this paper, two pressure sensors were added to the existing handheld OCT probe, and the imaging probe was fixed to a metal stand and adjusted vertically to change the pressure between the probe and the tested skin site, a gradient of roughly 4 kPa (with 1–2 kPa error) increase was applied in each experiment, and the impact of pressure to the vessel was calculated. The experiment involved a total of five subjects, three areas of which were scanned (palm, back of the hand, and forearm). The vessel density was calculated to evaluate the impact of external pressure on angiography. In addition, PSNR was calculated to ensure that the quality of different tests was at a similar level. The angiography showed the highest density (about 10%) when the pressure between the contact window on the probe and the test area was between 3 and 5 kPa. As the pressure increased, the vascular density decreased, and the rate of decrease varied in different test areas. After fitting all the data points according to the different sites, the slope of the fitted line, i.e., the rate of decrease in density per unit value of pressure, was found to be 4.05% at the palm site, 6.93% at the back of the hand, and 4.55% at the forearm site. This experiment demonstrates that the pressure between the skin and contact window is a significant parameter that cannot be ignored. It is recommended that in future OCTA data collection processes and probe designs, the impact of pressure on the experiment be considered

A hand‐held optical coherence tomography angiography scanner based on angiography reconstruction transformer networks

Optical coherence tomography angiography (OCTA) has successfully demonstrated its viability for clinical applications in dermatology. Due to the high optical scattering property of skin, extracting high‐quality OCTA images from skin tissues requires at least six‐repeated scans. While the motion artifacts from the patient and the free hand‐held probe can lead to a low‐quality OCTA image. Our deep‐learning‐based scan pipeline enables fast and high‐quality OCTA imaging with 0.3‐s data acquisition. We utilize a fast scanning protocol with a 60 μm/pixel spatial interval rate and introduce angiography‐reconstruction‐transformer (ART) for 4× super‐resolution of low transverse resolution OCTA images. The ART outperforms state‐of‐the‐art networks in OCTA image super‐resolution and provides a lighter network size. ART can restore microvessels while reducing the processing time by 85%, and maintaining improvements in structural similarity and peak‐signal‐to‐noise ratio. This study represents that ART can achieve fast and flexible skin OCTA imaging while maintaining image quality

A Fast Optical Coherence Tomography Angiography Image Acquisition and Reconstruction Pipeline for Skin Application

Traditional high-quality OCTA images require multi-repeated scans (e.g., 4-8 repeats) in the same position, which causes patient uncomfortable. We propose a deep-learning-based pipeline that can extract high-quality OCTA images from only two-repeat OCT scans. The performance of the proposed Image Reconstruction U-Net (IRU-Net) outperforms state-of-the-art UNet vision transformer and UNet in OCTA image reconstruction from a two-repeat OCT signal. The results demonstrated a mean peak-signal-to-noise ratio increased from 15.7 to 24.2; the mean structural similarity index measure improved from 0.28 to 0.59; while OCT data acquisition time was reduced from 21 seconds to 3.5 seconds (reduced by 83%)